Product Manager (Technical), Product Support Experience

Anthropic•San Francisco, CA

7h•$385,000 - $460,000•Hybrid

About The Position

Anthropic is hiring a Product Manager to build and own a world-class support experience for its customers and Product Support team. The role partners with Product Support Operations, AI Support, Billing, Fraud, and Product Engineering to build the systems that help users get unblocked, turn recurring support issues into product fixes, and enable Claude to operate as the primary support agent. The position owns the support experience end to end: Claude’s diagnosis and resolution or escalation of cases; surfacing recurring issues and preparing actionable bug reports; routing issues to engineering owners; following up with customers; and verifying that shipped fixes reduce case volume. The role defines the strategy and roadmap for the support-to-product feedback loop, the Claude support layer, escalation paths, and the metrics used to track contact rates, root-cause fixes, response times, and customer satisfaction. The goal is to reduce support cases per user and eliminate categories of cases as the product grows. This role calls for a product leader with at least seven years of product management experience and deep exposure to support systems, customer operations tooling, billing or payments, or internal operations platforms. The position is hybrid under Anthropic’s location-based policy: staff are currently expected to work from an office at least 25% of the time, with some roles potentially requiring more. A bachelor’s degree or an equivalent combination of education, training, and/or experience is the minimum education requirement; the field of study should be relevant to the role.

Requirements

At least 7 years of product management experience, with deep exposure to support systems, customer operations tooling, billing or payments, or internal platforms serving operations teams.
Experience taking technical platform products from infancy to scale for demanding internal or external engineering customers.
Track record of building products for multiple personas, making prioritization trade-offs, and communicating decisions clearly.
Ability to understand complex technical systems, including case routing, billing and payments flows, LLM-based agents, and data pipelines, and translate that understanding into a product vision.
Ability to work fluently across functions, including discussing technical traces with engineers, explaining prioritization to specialists, and communicating intake trends to leadership.
A strong perspective on how AI changes support, including the potential for an agent to diagnose, file, and fix issues behind customer cases.
Experience scaling an LLM-based product or experience from prototype to real volume, with an understanding of quality drift, cost, latency, and user trust challenges.
Resourcefulness and ability to get things done in a fast-moving environment.
Bachelor’s degree or an equivalent combination of education, training, and/or experience.
A field of study relevant to the role, demonstrated through coursework, training, or professional experience.

Nice To Haves

Built or scaled systems behind a high-volume support operation for consumer or developer products, such as case data pipelines, driver analytics, or LLM-based support agents.
Shipped an LLM-based support or operations agent in production and understand its trust, escalation, and quality-measurement challenges.
Defined and operationalized contact-rate or case-deflection metrics, with a perspective on how those metrics change when fixes ship in the product rather than the help center.
Scaled support-heavy environments through hypergrowth, such as consumer subscriptions, developer platforms, or fintech.
Experience getting product and engineering teams to own support drivers, with evidence of driving ownership through clear evidence and product quality.

Responsibilities

Understand the needs of Product Support Operations, AI Support, Billing, Fraud, and product engineering teams, from enterprise escalation specialists to engineers resolving support-related bugs.
Define and iterate on the support-to-product loop, including case classification, near-real-time detection of recurring drivers, case examples and recommended fixes, named ownership for each driver, and verification that fixes reduce case volume.
Own support metrics, including inbound case volume by driver, root-cause drivers fixed, and time from first report to shipped fix, alongside response-time and CSAT targets.
Own the customer experience of getting unblocked, including resolution speed and friction, whether Claude resolves a case or hands it to a specialist.
Limit the impact of novel issues by detecting early reports, assessing impact, and prioritizing fixes while the affected group is small.
Partner with engineering and data science to build scalable systems, including Claude as first responder, the driver-detection data pipeline, and tools for routing diagnosed cases to the right team.
Drive the strategy and roadmap for the in-house Claude support layer, including what it resolves, what it escalates and to whom, and how it supports filing and fixing underlying product issues.
Own the trade-off framework among intake reduction, response time, cost, and quality; make transparent prioritization decisions and communicate them to Product Support and senior leadership.
Develop and communicate a roadmap for support with Claude as the primary operator, ahead of anticipated support-volume growth.